[GitHub] [flink-web] zentol commented on a diff in pull request #641: Add blog article: Howto create a batch source with the new Source framework

["zentol (via GitHub)" <gi...@apache.org>]

zentol commented on code in PR #641:
URL: https://github.com/apache/flink-web/pull/641#discussion_r1166403021


##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch

Review Comment:
   ```suggestion
   lately. Some connectors have migrated to this new framework. This article is a how-to for creating a batch
   ```



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.

Review Comment:
   note to self: Re-phrase this; it reads too much like "don't read this".



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has

Review Comment:
   ```suggestion
   The Flink community has
   ```



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to

Review Comment:
   It is not clear which "main thread" this is referring to.



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the

Review Comment:
   ```suggestion
   Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
   ```



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.
+
+What we have left to do in the SourceReader class is:
+* Provide a [SplitReader](#splitreader) supplier
+* Create a [RecordEmitter](#recordemitter)
+* Create the shared resources for the SplitReaders (sessions, etc...). As the SplitReader supplier is
+created in the SourceReader constructor in a super() call, using a SourceReader factory to create
+the shared resources and pass them to the supplier seems a good idea.

Review Comment:
   ```suggestion
   the shared resources and pass them to the supplier is a good idea.
   ```



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.

Review Comment:
   > read splits with one thread using one [SplitReader]
   
   > This is not harmful to the performance of the source as the SourceReaders run in
   parallel among the task managers.
   
   This sounds contradicting.



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.
+
+What we have left to do in the SourceReader class is:
+* Provide a [SplitReader](#splitreader) supplier
+* Create a [RecordEmitter](#recordemitter)
+* Create the shared resources for the SplitReaders (sessions, etc...). As the SplitReader supplier is
+created in the SourceReader constructor in a super() call, using a SourceReader factory to create
+the shared resources and pass them to the supplier seems a good idea.
+* Implement [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html#start--): here we should ask the enumerator for our first split
+* Override [close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#close--) in SourceReaderBase parent class to free up any created resources (the shared
+resources for example)
+* Implement [initializedState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#initializedState-SplitT-) to create a mutable [SplitState](#split-and-splitstate) from a Split
+* Implement [toSplitType()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#toSplitType-java.lang.String-SplitStateT-) to create a Split from the mutable SplitState
+* Implement [onSplitFinished()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#onSplitFinished-java.util.Map-): here, as it is a batch source (finite data), we should ask the
+Enumerator for next split
+
+### Split and SplitState
+[example Cassandra Split](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplit.java)
+
+The [SourceSplit](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceSplit.html) represents a partition of the source data. What defines a split depends on the
+backend we are reading from. It could be a _(partition start, partition end)_ tuple or an _(offset,
+split size)_ tuple for example.
+
+In any case, the Split object should be seen as an immutable object: any update to it should be done
+on the associated [SplitState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html). The split state is the one that will be stored inside the Flink
+[checkpoints](https://nightlies.apache.org/flink/flink-docs-master/docs/concepts/stateful-stream-processing/#checkpointing). A checkpoint may happen between 2 fetches for 1 split. So, if we're reading a split, we
+must store in the split state the current state of the reading process. This current state needs to
+be something serializable (because it will be part of a checkpoint) and something that the backend
+source can resume from. That way, in case of failover, the reading could be resumed from where it
+was left off. Thus we ensure there will be no duplicates or lost data. For example, if the records
+reading order is deterministic in the backend, then the split state can store the number _n_ of
+already read records to restart at _n+1_ after failover. 
+
+### SplitEnumerator and SplitEnumeratorState
+[example Cassandra SplitEnumerator](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraSplitEnumerator.java) and [SplitEnumeratorState](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorState.java)
+
+The [SplitEnumerator](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html) is responsible for creating the splits and serving them to the readers. Whenever
+possible, it is preferable to generate the splits lazily, meaning that each time a reader asks the
+enumerator for a split, the enumerator generates one on demand and assigns it to the reader. For
+that we implement [SplitEnumerator#handleSplitRequest()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#handleSplitRequest-int-java.lang.String-). Lazy splits generation is preferable to
+splits discovery, in which we pre-generate all the splits and store them waiting to assign them to
+the readers. Indeed, in some situations, the number of splits can be enormous at consume a lot a
+memory which could be problematic in case of straggling readers. The framework offers the ability to
+act upon reader registration by implementing [addReader()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addReader-int-) but, as we do lazy splits generation, we
+have nothing to do there. In some case, generating a split is too costly, so we can pre-generate a
+batch (not all) of splits to amortize this cost. the number/size of batched splits need to be taken
+into account to avoid consuming too much memory.
+
+Long story short, the tricky part of the source implementation is splitting the source data. The
+good equilibrium to find is not to have to many splits (which could lead to too much memory
+consumption) nor too few (which could lead to sub-optimal parallelism). One good way to meet this
+equilibrium is to evaluate the size of the source data upfront and allow the user to specify the
+maximum memory a split will take. That way he can configure this parameter accordingly to the memory
+available on the task managers. Of course, the size of the source data needs to be evaluated without
+reading the actual data. For the Cassandra connector it was done [like this](https://echauchot.blogspot.com/2023/03/cassandra-evaluate-table-size-without.html). The general rule of thumb
+regarding splitting is to let the user some freedom but protect him from unwanted behavior: if he

Review Comment:
   ```suggestion
   regarding splitting is to let the user some freedom but protect him from unwanted behavior: if they
   ```



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one

Review Comment:
   It's not clear why the threading model is a concern.



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.
+
+What we have left to do in the SourceReader class is:
+* Provide a [SplitReader](#splitreader) supplier
+* Create a [RecordEmitter](#recordemitter)
+* Create the shared resources for the SplitReaders (sessions, etc...). As the SplitReader supplier is
+created in the SourceReader constructor in a super() call, using a SourceReader factory to create
+the shared resources and pass them to the supplier seems a good idea.
+* Implement [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html#start--): here we should ask the enumerator for our first split
+* Override [close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#close--) in SourceReaderBase parent class to free up any created resources (the shared
+resources for example)
+* Implement [initializedState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#initializedState-SplitT-) to create a mutable [SplitState](#split-and-splitstate) from a Split
+* Implement [toSplitType()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#toSplitType-java.lang.String-SplitStateT-) to create a Split from the mutable SplitState
+* Implement [onSplitFinished()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#onSplitFinished-java.util.Map-): here, as it is a batch source (finite data), we should ask the
+Enumerator for next split
+
+### Split and SplitState
+[example Cassandra Split](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplit.java)
+
+The [SourceSplit](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceSplit.html) represents a partition of the source data. What defines a split depends on the
+backend we are reading from. It could be a _(partition start, partition end)_ tuple or an _(offset,
+split size)_ tuple for example.
+
+In any case, the Split object should be seen as an immutable object: any update to it should be done
+on the associated [SplitState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html). The split state is the one that will be stored inside the Flink
+[checkpoints](https://nightlies.apache.org/flink/flink-docs-master/docs/concepts/stateful-stream-processing/#checkpointing). A checkpoint may happen between 2 fetches for 1 split. So, if we're reading a split, we
+must store in the split state the current state of the reading process. This current state needs to
+be something serializable (because it will be part of a checkpoint) and something that the backend
+source can resume from. That way, in case of failover, the reading could be resumed from where it
+was left off. Thus we ensure there will be no duplicates or lost data. For example, if the records
+reading order is deterministic in the backend, then the split state can store the number _n_ of
+already read records to restart at _n+1_ after failover. 
+
+### SplitEnumerator and SplitEnumeratorState
+[example Cassandra SplitEnumerator](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraSplitEnumerator.java) and [SplitEnumeratorState](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorState.java)
+
+The [SplitEnumerator](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html) is responsible for creating the splits and serving them to the readers. Whenever
+possible, it is preferable to generate the splits lazily, meaning that each time a reader asks the
+enumerator for a split, the enumerator generates one on demand and assigns it to the reader. For
+that we implement [SplitEnumerator#handleSplitRequest()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#handleSplitRequest-int-java.lang.String-). Lazy splits generation is preferable to
+splits discovery, in which we pre-generate all the splits and store them waiting to assign them to
+the readers. Indeed, in some situations, the number of splits can be enormous at consume a lot a
+memory which could be problematic in case of straggling readers. The framework offers the ability to
+act upon reader registration by implementing [addReader()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addReader-int-) but, as we do lazy splits generation, we
+have nothing to do there. In some case, generating a split is too costly, so we can pre-generate a
+batch (not all) of splits to amortize this cost. the number/size of batched splits need to be taken
+into account to avoid consuming too much memory.
+
+Long story short, the tricky part of the source implementation is splitting the source data. The
+good equilibrium to find is not to have to many splits (which could lead to too much memory
+consumption) nor too few (which could lead to sub-optimal parallelism). One good way to meet this
+equilibrium is to evaluate the size of the source data upfront and allow the user to specify the
+maximum memory a split will take. That way he can configure this parameter accordingly to the memory
+available on the task managers. Of course, the size of the source data needs to be evaluated without
+reading the actual data. For the Cassandra connector it was done [like this](https://echauchot.blogspot.com/2023/03/cassandra-evaluate-table-size-without.html). The general rule of thumb
+regarding splitting is to let the user some freedom but protect him from unwanted behavior: if he
+wants to process a 1GB table in 1MB splits with 1 subtask he should be free to do so. But, as we

Review Comment:
   ```suggestion
   want to process a 1GB table in 1MB splits with 1 subtask they should be free to do so. But, as we
   ```



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.
+
+What we have left to do in the SourceReader class is:
+* Provide a [SplitReader](#splitreader) supplier
+* Create a [RecordEmitter](#recordemitter)
+* Create the shared resources for the SplitReaders (sessions, etc...). As the SplitReader supplier is
+created in the SourceReader constructor in a super() call, using a SourceReader factory to create
+the shared resources and pass them to the supplier seems a good idea.
+* Implement [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html#start--): here we should ask the enumerator for our first split
+* Override [close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#close--) in SourceReaderBase parent class to free up any created resources (the shared
+resources for example)
+* Implement [initializedState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#initializedState-SplitT-) to create a mutable [SplitState](#split-and-splitstate) from a Split
+* Implement [toSplitType()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#toSplitType-java.lang.String-SplitStateT-) to create a Split from the mutable SplitState
+* Implement [onSplitFinished()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#onSplitFinished-java.util.Map-): here, as it is a batch source (finite data), we should ask the
+Enumerator for next split
+
+### Split and SplitState
+[example Cassandra Split](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplit.java)
+
+The [SourceSplit](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceSplit.html) represents a partition of the source data. What defines a split depends on the
+backend we are reading from. It could be a _(partition start, partition end)_ tuple or an _(offset,
+split size)_ tuple for example.
+
+In any case, the Split object should be seen as an immutable object: any update to it should be done
+on the associated [SplitState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html). The split state is the one that will be stored inside the Flink
+[checkpoints](https://nightlies.apache.org/flink/flink-docs-master/docs/concepts/stateful-stream-processing/#checkpointing). A checkpoint may happen between 2 fetches for 1 split. So, if we're reading a split, we
+must store in the split state the current state of the reading process. This current state needs to
+be something serializable (because it will be part of a checkpoint) and something that the backend
+source can resume from. That way, in case of failover, the reading could be resumed from where it
+was left off. Thus we ensure there will be no duplicates or lost data. For example, if the records
+reading order is deterministic in the backend, then the split state can store the number _n_ of
+already read records to restart at _n+1_ after failover. 
+
+### SplitEnumerator and SplitEnumeratorState
+[example Cassandra SplitEnumerator](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraSplitEnumerator.java) and [SplitEnumeratorState](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorState.java)
+
+The [SplitEnumerator](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html) is responsible for creating the splits and serving them to the readers. Whenever
+possible, it is preferable to generate the splits lazily, meaning that each time a reader asks the
+enumerator for a split, the enumerator generates one on demand and assigns it to the reader. For
+that we implement [SplitEnumerator#handleSplitRequest()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#handleSplitRequest-int-java.lang.String-). Lazy splits generation is preferable to
+splits discovery, in which we pre-generate all the splits and store them waiting to assign them to
+the readers. Indeed, in some situations, the number of splits can be enormous at consume a lot a
+memory which could be problematic in case of straggling readers. The framework offers the ability to
+act upon reader registration by implementing [addReader()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addReader-int-) but, as we do lazy splits generation, we
+have nothing to do there. In some case, generating a split is too costly, so we can pre-generate a
+batch (not all) of splits to amortize this cost. the number/size of batched splits need to be taken

Review Comment:
   ```suggestion
   batch (not all) of splits to amortize this cost. The number/size of batched splits need to be taken
   ```



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.
+
+What we have left to do in the SourceReader class is:
+* Provide a [SplitReader](#splitreader) supplier
+* Create a [RecordEmitter](#recordemitter)
+* Create the shared resources for the SplitReaders (sessions, etc...). As the SplitReader supplier is
+created in the SourceReader constructor in a super() call, using a SourceReader factory to create
+the shared resources and pass them to the supplier seems a good idea.
+* Implement [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html#start--): here we should ask the enumerator for our first split
+* Override [close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#close--) in SourceReaderBase parent class to free up any created resources (the shared
+resources for example)
+* Implement [initializedState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#initializedState-SplitT-) to create a mutable [SplitState](#split-and-splitstate) from a Split
+* Implement [toSplitType()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#toSplitType-java.lang.String-SplitStateT-) to create a Split from the mutable SplitState
+* Implement [onSplitFinished()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#onSplitFinished-java.util.Map-): here, as it is a batch source (finite data), we should ask the
+Enumerator for next split
+
+### Split and SplitState
+[example Cassandra Split](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplit.java)
+
+The [SourceSplit](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceSplit.html) represents a partition of the source data. What defines a split depends on the
+backend we are reading from. It could be a _(partition start, partition end)_ tuple or an _(offset,
+split size)_ tuple for example.
+
+In any case, the Split object should be seen as an immutable object: any update to it should be done
+on the associated [SplitState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html). The split state is the one that will be stored inside the Flink
+[checkpoints](https://nightlies.apache.org/flink/flink-docs-master/docs/concepts/stateful-stream-processing/#checkpointing). A checkpoint may happen between 2 fetches for 1 split. So, if we're reading a split, we
+must store in the split state the current state of the reading process. This current state needs to
+be something serializable (because it will be part of a checkpoint) and something that the backend
+source can resume from. That way, in case of failover, the reading could be resumed from where it
+was left off. Thus we ensure there will be no duplicates or lost data. For example, if the records
+reading order is deterministic in the backend, then the split state can store the number _n_ of
+already read records to restart at _n+1_ after failover. 
+
+### SplitEnumerator and SplitEnumeratorState
+[example Cassandra SplitEnumerator](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraSplitEnumerator.java) and [SplitEnumeratorState](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorState.java)
+
+The [SplitEnumerator](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html) is responsible for creating the splits and serving them to the readers. Whenever
+possible, it is preferable to generate the splits lazily, meaning that each time a reader asks the
+enumerator for a split, the enumerator generates one on demand and assigns it to the reader. For
+that we implement [SplitEnumerator#handleSplitRequest()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#handleSplitRequest-int-java.lang.String-). Lazy splits generation is preferable to
+splits discovery, in which we pre-generate all the splits and store them waiting to assign them to
+the readers. Indeed, in some situations, the number of splits can be enormous at consume a lot a
+memory which could be problematic in case of straggling readers. The framework offers the ability to
+act upon reader registration by implementing [addReader()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addReader-int-) but, as we do lazy splits generation, we
+have nothing to do there. In some case, generating a split is too costly, so we can pre-generate a
+batch (not all) of splits to amortize this cost. the number/size of batched splits need to be taken
+into account to avoid consuming too much memory.
+
+Long story short, the tricky part of the source implementation is splitting the source data. The
+good equilibrium to find is not to have to many splits (which could lead to too much memory
+consumption) nor too few (which could lead to sub-optimal parallelism). One good way to meet this
+equilibrium is to evaluate the size of the source data upfront and allow the user to specify the
+maximum memory a split will take. That way he can configure this parameter accordingly to the memory
+available on the task managers. Of course, the size of the source data needs to be evaluated without
+reading the actual data. For the Cassandra connector it was done [like this](https://echauchot.blogspot.com/2023/03/cassandra-evaluate-table-size-without.html). The general rule of thumb
+regarding splitting is to let the user some freedom but protect him from unwanted behavior: if he
+wants to process a 1GB table in 1MB splits with 1 subtask he should be free to do so. But, as we
+allow the user to set a max split size, we should still ensure it is not too small to avoid having
+too many splits, we must also provide a default maximum. For these safety measures, rigid thresholds
+don't work well as the source my start to fail when the thresholds are suddenly exceeded.

Review Comment:
   ```suggestion
   don't work well as the source may start to fail when the thresholds are suddenly exceeded.
   ```
   
   Maybe add an example for when this would happen; like a periodically run job on a growing table.



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.
+
+What we have left to do in the SourceReader class is:
+* Provide a [SplitReader](#splitreader) supplier
+* Create a [RecordEmitter](#recordemitter)
+* Create the shared resources for the SplitReaders (sessions, etc...). As the SplitReader supplier is
+created in the SourceReader constructor in a super() call, using a SourceReader factory to create
+the shared resources and pass them to the supplier seems a good idea.
+* Implement [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html#start--): here we should ask the enumerator for our first split
+* Override [close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#close--) in SourceReaderBase parent class to free up any created resources (the shared
+resources for example)
+* Implement [initializedState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#initializedState-SplitT-) to create a mutable [SplitState](#split-and-splitstate) from a Split
+* Implement [toSplitType()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#toSplitType-java.lang.String-SplitStateT-) to create a Split from the mutable SplitState
+* Implement [onSplitFinished()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#onSplitFinished-java.util.Map-): here, as it is a batch source (finite data), we should ask the
+Enumerator for next split
+
+### Split and SplitState
+[example Cassandra Split](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplit.java)
+
+The [SourceSplit](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceSplit.html) represents a partition of the source data. What defines a split depends on the
+backend we are reading from. It could be a _(partition start, partition end)_ tuple or an _(offset,
+split size)_ tuple for example.
+
+In any case, the Split object should be seen as an immutable object: any update to it should be done
+on the associated [SplitState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html). The split state is the one that will be stored inside the Flink
+[checkpoints](https://nightlies.apache.org/flink/flink-docs-master/docs/concepts/stateful-stream-processing/#checkpointing). A checkpoint may happen between 2 fetches for 1 split. So, if we're reading a split, we
+must store in the split state the current state of the reading process. This current state needs to
+be something serializable (because it will be part of a checkpoint) and something that the backend
+source can resume from. That way, in case of failover, the reading could be resumed from where it
+was left off. Thus we ensure there will be no duplicates or lost data. For example, if the records
+reading order is deterministic in the backend, then the split state can store the number _n_ of
+already read records to restart at _n+1_ after failover. 
+
+### SplitEnumerator and SplitEnumeratorState
+[example Cassandra SplitEnumerator](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraSplitEnumerator.java) and [SplitEnumeratorState](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorState.java)
+
+The [SplitEnumerator](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html) is responsible for creating the splits and serving them to the readers. Whenever
+possible, it is preferable to generate the splits lazily, meaning that each time a reader asks the
+enumerator for a split, the enumerator generates one on demand and assigns it to the reader. For
+that we implement [SplitEnumerator#handleSplitRequest()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#handleSplitRequest-int-java.lang.String-). Lazy splits generation is preferable to
+splits discovery, in which we pre-generate all the splits and store them waiting to assign them to
+the readers. Indeed, in some situations, the number of splits can be enormous at consume a lot a
+memory which could be problematic in case of straggling readers. The framework offers the ability to
+act upon reader registration by implementing [addReader()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addReader-int-) but, as we do lazy splits generation, we
+have nothing to do there. In some case, generating a split is too costly, so we can pre-generate a
+batch (not all) of splits to amortize this cost. the number/size of batched splits need to be taken
+into account to avoid consuming too much memory.
+
+Long story short, the tricky part of the source implementation is splitting the source data. The
+good equilibrium to find is not to have to many splits (which could lead to too much memory
+consumption) nor too few (which could lead to sub-optimal parallelism). One good way to meet this
+equilibrium is to evaluate the size of the source data upfront and allow the user to specify the
+maximum memory a split will take. That way he can configure this parameter accordingly to the memory
+available on the task managers. Of course, the size of the source data needs to be evaluated without
+reading the actual data. For the Cassandra connector it was done [like this](https://echauchot.blogspot.com/2023/03/cassandra-evaluate-table-size-without.html). The general rule of thumb
+regarding splitting is to let the user some freedom but protect him from unwanted behavior: if he
+wants to process a 1GB table in 1MB splits with 1 subtask he should be free to do so. But, as we
+allow the user to set a max split size, we should still ensure it is not too small to avoid having
+too many splits, we must also provide a default maximum. For these safety measures, rigid thresholds

Review Comment:
   It is not clear why a default maximum ensures that splits aren't too small.



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.
+
+What we have left to do in the SourceReader class is:
+* Provide a [SplitReader](#splitreader) supplier
+* Create a [RecordEmitter](#recordemitter)
+* Create the shared resources for the SplitReaders (sessions, etc...). As the SplitReader supplier is
+created in the SourceReader constructor in a super() call, using a SourceReader factory to create
+the shared resources and pass them to the supplier seems a good idea.
+* Implement [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html#start--): here we should ask the enumerator for our first split
+* Override [close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#close--) in SourceReaderBase parent class to free up any created resources (the shared
+resources for example)
+* Implement [initializedState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#initializedState-SplitT-) to create a mutable [SplitState](#split-and-splitstate) from a Split
+* Implement [toSplitType()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#toSplitType-java.lang.String-SplitStateT-) to create a Split from the mutable SplitState
+* Implement [onSplitFinished()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#onSplitFinished-java.util.Map-): here, as it is a batch source (finite data), we should ask the
+Enumerator for next split
+
+### Split and SplitState
+[example Cassandra Split](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplit.java)
+
+The [SourceSplit](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceSplit.html) represents a partition of the source data. What defines a split depends on the
+backend we are reading from. It could be a _(partition start, partition end)_ tuple or an _(offset,
+split size)_ tuple for example.
+
+In any case, the Split object should be seen as an immutable object: any update to it should be done
+on the associated [SplitState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html). The split state is the one that will be stored inside the Flink
+[checkpoints](https://nightlies.apache.org/flink/flink-docs-master/docs/concepts/stateful-stream-processing/#checkpointing). A checkpoint may happen between 2 fetches for 1 split. So, if we're reading a split, we
+must store in the split state the current state of the reading process. This current state needs to
+be something serializable (because it will be part of a checkpoint) and something that the backend
+source can resume from. That way, in case of failover, the reading could be resumed from where it
+was left off. Thus we ensure there will be no duplicates or lost data. For example, if the records
+reading order is deterministic in the backend, then the split state can store the number _n_ of
+already read records to restart at _n+1_ after failover. 
+
+### SplitEnumerator and SplitEnumeratorState
+[example Cassandra SplitEnumerator](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraSplitEnumerator.java) and [SplitEnumeratorState](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorState.java)
+
+The [SplitEnumerator](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html) is responsible for creating the splits and serving them to the readers. Whenever
+possible, it is preferable to generate the splits lazily, meaning that each time a reader asks the
+enumerator for a split, the enumerator generates one on demand and assigns it to the reader. For
+that we implement [SplitEnumerator#handleSplitRequest()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#handleSplitRequest-int-java.lang.String-). Lazy splits generation is preferable to
+splits discovery, in which we pre-generate all the splits and store them waiting to assign them to
+the readers. Indeed, in some situations, the number of splits can be enormous at consume a lot a
+memory which could be problematic in case of straggling readers. The framework offers the ability to
+act upon reader registration by implementing [addReader()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addReader-int-) but, as we do lazy splits generation, we
+have nothing to do there. In some case, generating a split is too costly, so we can pre-generate a
+batch (not all) of splits to amortize this cost. the number/size of batched splits need to be taken
+into account to avoid consuming too much memory.
+
+Long story short, the tricky part of the source implementation is splitting the source data. The
+good equilibrium to find is not to have to many splits (which could lead to too much memory
+consumption) nor too few (which could lead to sub-optimal parallelism). One good way to meet this
+equilibrium is to evaluate the size of the source data upfront and allow the user to specify the
+maximum memory a split will take. That way he can configure this parameter accordingly to the memory
+available on the task managers. Of course, the size of the source data needs to be evaluated without
+reading the actual data. For the Cassandra connector it was done [like this](https://echauchot.blogspot.com/2023/03/cassandra-evaluate-table-size-without.html). The general rule of thumb
+regarding splitting is to let the user some freedom but protect him from unwanted behavior: if he
+wants to process a 1GB table in 1MB splits with 1 subtask he should be free to do so. But, as we
+allow the user to set a max split size, we should still ensure it is not too small to avoid having
+too many splits, we must also provide a default maximum. For these safety measures, rigid thresholds
+don't work well as the source my start to fail when the thresholds are suddenly exceeded.
+
+Another important topic is state. If the job manager fails, the split enumerator needs to recover.
+For that, as for the split, we need to provide a state for the enumerator (that will be part of a
+checkpoint) and return it when [SplitEnumerator#snapshotState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#snapshotState-long-) is called. Here also the
+SplitEnumerator is to be considered immutable. Any update to the state of the SplitEnumerator, must
+be done in the associated [SplitEnumeratorState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html). So, we don't create the state when snapshotState()
+is called but rather in the enumerator's constructor and return it in snapshotState(). The state

Review Comment:
   It's not clear _why_ this should be done.
   
   There's strictly speaking no requirement for the `SplitEnumerator` to be immutable.
   They can convert the `SplitEnumeratorState` given via the constructor to some internal mutable representation, and return a completely new `SplitEnumeratorState` in `snapshotState()`.
   
   Some would argue that the `SplitEnumeratorState` should be immutable, because that is data being passed to other components.



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.
+
+What we have left to do in the SourceReader class is:
+* Provide a [SplitReader](#splitreader) supplier
+* Create a [RecordEmitter](#recordemitter)
+* Create the shared resources for the SplitReaders (sessions, etc...). As the SplitReader supplier is
+created in the SourceReader constructor in a super() call, using a SourceReader factory to create
+the shared resources and pass them to the supplier seems a good idea.
+* Implement [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html#start--): here we should ask the enumerator for our first split
+* Override [close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#close--) in SourceReaderBase parent class to free up any created resources (the shared
+resources for example)
+* Implement [initializedState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#initializedState-SplitT-) to create a mutable [SplitState](#split-and-splitstate) from a Split
+* Implement [toSplitType()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#toSplitType-java.lang.String-SplitStateT-) to create a Split from the mutable SplitState
+* Implement [onSplitFinished()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#onSplitFinished-java.util.Map-): here, as it is a batch source (finite data), we should ask the
+Enumerator for next split
+
+### Split and SplitState
+[example Cassandra Split](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplit.java)
+
+The [SourceSplit](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceSplit.html) represents a partition of the source data. What defines a split depends on the
+backend we are reading from. It could be a _(partition start, partition end)_ tuple or an _(offset,
+split size)_ tuple for example.
+
+In any case, the Split object should be seen as an immutable object: any update to it should be done
+on the associated [SplitState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html). The split state is the one that will be stored inside the Flink
+[checkpoints](https://nightlies.apache.org/flink/flink-docs-master/docs/concepts/stateful-stream-processing/#checkpointing). A checkpoint may happen between 2 fetches for 1 split. So, if we're reading a split, we
+must store in the split state the current state of the reading process. This current state needs to
+be something serializable (because it will be part of a checkpoint) and something that the backend
+source can resume from. That way, in case of failover, the reading could be resumed from where it
+was left off. Thus we ensure there will be no duplicates or lost data. For example, if the records
+reading order is deterministic in the backend, then the split state can store the number _n_ of
+already read records to restart at _n+1_ after failover. 
+
+### SplitEnumerator and SplitEnumeratorState
+[example Cassandra SplitEnumerator](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraSplitEnumerator.java) and [SplitEnumeratorState](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorState.java)
+
+The [SplitEnumerator](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html) is responsible for creating the splits and serving them to the readers. Whenever
+possible, it is preferable to generate the splits lazily, meaning that each time a reader asks the
+enumerator for a split, the enumerator generates one on demand and assigns it to the reader. For
+that we implement [SplitEnumerator#handleSplitRequest()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#handleSplitRequest-int-java.lang.String-). Lazy splits generation is preferable to
+splits discovery, in which we pre-generate all the splits and store them waiting to assign them to
+the readers. Indeed, in some situations, the number of splits can be enormous at consume a lot a
+memory which could be problematic in case of straggling readers. The framework offers the ability to
+act upon reader registration by implementing [addReader()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addReader-int-) but, as we do lazy splits generation, we
+have nothing to do there. In some case, generating a split is too costly, so we can pre-generate a
+batch (not all) of splits to amortize this cost. the number/size of batched splits need to be taken
+into account to avoid consuming too much memory.
+
+Long story short, the tricky part of the source implementation is splitting the source data. The
+good equilibrium to find is not to have to many splits (which could lead to too much memory
+consumption) nor too few (which could lead to sub-optimal parallelism). One good way to meet this
+equilibrium is to evaluate the size of the source data upfront and allow the user to specify the
+maximum memory a split will take. That way he can configure this parameter accordingly to the memory
+available on the task managers. Of course, the size of the source data needs to be evaluated without
+reading the actual data. For the Cassandra connector it was done [like this](https://echauchot.blogspot.com/2023/03/cassandra-evaluate-table-size-without.html). The general rule of thumb
+regarding splitting is to let the user some freedom but protect him from unwanted behavior: if he
+wants to process a 1GB table in 1MB splits with 1 subtask he should be free to do so. But, as we
+allow the user to set a max split size, we should still ensure it is not too small to avoid having
+too many splits, we must also provide a default maximum. For these safety measures, rigid thresholds
+don't work well as the source my start to fail when the thresholds are suddenly exceeded.
+
+Another important topic is state. If the job manager fails, the split enumerator needs to recover.
+For that, as for the split, we need to provide a state for the enumerator (that will be part of a
+checkpoint) and return it when [SplitEnumerator#snapshotState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#snapshotState-long-) is called. Here also the
+SplitEnumerator is to be considered immutable. Any update to the state of the SplitEnumerator, must
+be done in the associated [SplitEnumeratorState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html). So, we don't create the state when snapshotState()
+is called but rather in the enumerator's constructor and return it in snapshotState(). The state
+must contain everything needed to resume where the enumerator was left off after failover . In lazy
+split generation scenario, the state will contain everything needed to generate the next split
+whenever asked to. It can be for example the start offset of next split, split size, number of
+splits still to generate etc... But the SplitEnumeratorState must also contain a list of splits, not
+the list of discovered splits, but a list of splits to reassign. Indeed, whenever a reader fails, if
+it was assigned splits after last chekpoint, then the checkpoint will not contain those splits.
+Consequently, upon restoration, the reader won't have the splits assigned anymore. There is a
+callback to deal with that case: [addSplitsBack()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addSplitsBack-java.util.List-int-). There, the splits that were assigned to the
+failing reader, can be put back into the enumerator state for later re-assignment to readers. There
+is no memory size risk here as the number of splits to reassign is pretty low.
+
+The above topics are the more important regarding splitting. There are 2 methods left to implement:
+the usual [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#start--)/[close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#close--) methods for resources creation/disposal. Regarding implementing start(),
+the Flink connector framework provides [enumeratorContext#callAsync()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumeratorContext.html#callAsync-java.util.concurrent.Callable-java.util.function.BiConsumer-long-long-) utility to run long processing
+asynchronously such as splits preparation or splits discovery (if lazy splits generation is

Review Comment:
   "Why would I want to do that?"



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.
+
+What we have left to do in the SourceReader class is:
+* Provide a [SplitReader](#splitreader) supplier
+* Create a [RecordEmitter](#recordemitter)
+* Create the shared resources for the SplitReaders (sessions, etc...). As the SplitReader supplier is
+created in the SourceReader constructor in a super() call, using a SourceReader factory to create
+the shared resources and pass them to the supplier seems a good idea.
+* Implement [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html#start--): here we should ask the enumerator for our first split
+* Override [close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#close--) in SourceReaderBase parent class to free up any created resources (the shared
+resources for example)
+* Implement [initializedState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#initializedState-SplitT-) to create a mutable [SplitState](#split-and-splitstate) from a Split
+* Implement [toSplitType()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#toSplitType-java.lang.String-SplitStateT-) to create a Split from the mutable SplitState
+* Implement [onSplitFinished()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#onSplitFinished-java.util.Map-): here, as it is a batch source (finite data), we should ask the
+Enumerator for next split
+
+### Split and SplitState
+[example Cassandra Split](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplit.java)
+
+The [SourceSplit](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceSplit.html) represents a partition of the source data. What defines a split depends on the
+backend we are reading from. It could be a _(partition start, partition end)_ tuple or an _(offset,
+split size)_ tuple for example.
+
+In any case, the Split object should be seen as an immutable object: any update to it should be done
+on the associated [SplitState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html). The split state is the one that will be stored inside the Flink
+[checkpoints](https://nightlies.apache.org/flink/flink-docs-master/docs/concepts/stateful-stream-processing/#checkpointing). A checkpoint may happen between 2 fetches for 1 split. So, if we're reading a split, we
+must store in the split state the current state of the reading process. This current state needs to
+be something serializable (because it will be part of a checkpoint) and something that the backend
+source can resume from. That way, in case of failover, the reading could be resumed from where it
+was left off. Thus we ensure there will be no duplicates or lost data. For example, if the records
+reading order is deterministic in the backend, then the split state can store the number _n_ of
+already read records to restart at _n+1_ after failover. 
+
+### SplitEnumerator and SplitEnumeratorState
+[example Cassandra SplitEnumerator](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraSplitEnumerator.java) and [SplitEnumeratorState](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorState.java)
+
+The [SplitEnumerator](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html) is responsible for creating the splits and serving them to the readers. Whenever
+possible, it is preferable to generate the splits lazily, meaning that each time a reader asks the
+enumerator for a split, the enumerator generates one on demand and assigns it to the reader. For
+that we implement [SplitEnumerator#handleSplitRequest()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#handleSplitRequest-int-java.lang.String-). Lazy splits generation is preferable to
+splits discovery, in which we pre-generate all the splits and store them waiting to assign them to
+the readers. Indeed, in some situations, the number of splits can be enormous at consume a lot a
+memory which could be problematic in case of straggling readers. The framework offers the ability to
+act upon reader registration by implementing [addReader()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addReader-int-) but, as we do lazy splits generation, we
+have nothing to do there. In some case, generating a split is too costly, so we can pre-generate a
+batch (not all) of splits to amortize this cost. the number/size of batched splits need to be taken
+into account to avoid consuming too much memory.
+
+Long story short, the tricky part of the source implementation is splitting the source data. The
+good equilibrium to find is not to have to many splits (which could lead to too much memory
+consumption) nor too few (which could lead to sub-optimal parallelism). One good way to meet this
+equilibrium is to evaluate the size of the source data upfront and allow the user to specify the
+maximum memory a split will take. That way he can configure this parameter accordingly to the memory
+available on the task managers. Of course, the size of the source data needs to be evaluated without
+reading the actual data. For the Cassandra connector it was done [like this](https://echauchot.blogspot.com/2023/03/cassandra-evaluate-table-size-without.html). The general rule of thumb
+regarding splitting is to let the user some freedom but protect him from unwanted behavior: if he
+wants to process a 1GB table in 1MB splits with 1 subtask he should be free to do so. But, as we
+allow the user to set a max split size, we should still ensure it is not too small to avoid having
+too many splits, we must also provide a default maximum. For these safety measures, rigid thresholds
+don't work well as the source my start to fail when the thresholds are suddenly exceeded.
+
+Another important topic is state. If the job manager fails, the split enumerator needs to recover.
+For that, as for the split, we need to provide a state for the enumerator (that will be part of a
+checkpoint) and return it when [SplitEnumerator#snapshotState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#snapshotState-long-) is called. Here also the
+SplitEnumerator is to be considered immutable. Any update to the state of the SplitEnumerator, must
+be done in the associated [SplitEnumeratorState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html). So, we don't create the state when snapshotState()
+is called but rather in the enumerator's constructor and return it in snapshotState(). The state
+must contain everything needed to resume where the enumerator was left off after failover . In lazy

Review Comment:
   ```suggestion
   must contain everything needed to resume where the enumerator was left off after failover. In lazy
   ```



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.

Review Comment:
   ```suggestion
   for [Cassandra](https://cassandra.apache.org/_/index.html).
   If you are interested in contributing or migrating connectors, this blog post is for you!.
   ```



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.
+
+What we have left to do in the SourceReader class is:
+* Provide a [SplitReader](#splitreader) supplier
+* Create a [RecordEmitter](#recordemitter)
+* Create the shared resources for the SplitReaders (sessions, etc...). As the SplitReader supplier is
+created in the SourceReader constructor in a super() call, using a SourceReader factory to create
+the shared resources and pass them to the supplier seems a good idea.
+* Implement [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html#start--): here we should ask the enumerator for our first split
+* Override [close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#close--) in SourceReaderBase parent class to free up any created resources (the shared
+resources for example)
+* Implement [initializedState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#initializedState-SplitT-) to create a mutable [SplitState](#split-and-splitstate) from a Split
+* Implement [toSplitType()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#toSplitType-java.lang.String-SplitStateT-) to create a Split from the mutable SplitState
+* Implement [onSplitFinished()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#onSplitFinished-java.util.Map-): here, as it is a batch source (finite data), we should ask the
+Enumerator for next split
+
+### Split and SplitState
+[example Cassandra Split](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplit.java)
+
+The [SourceSplit](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceSplit.html) represents a partition of the source data. What defines a split depends on the
+backend we are reading from. It could be a _(partition start, partition end)_ tuple or an _(offset,
+split size)_ tuple for example.
+
+In any case, the Split object should be seen as an immutable object: any update to it should be done
+on the associated [SplitState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html). The split state is the one that will be stored inside the Flink
+[checkpoints](https://nightlies.apache.org/flink/flink-docs-master/docs/concepts/stateful-stream-processing/#checkpointing). A checkpoint may happen between 2 fetches for 1 split. So, if we're reading a split, we
+must store in the split state the current state of the reading process. This current state needs to
+be something serializable (because it will be part of a checkpoint) and something that the backend
+source can resume from. That way, in case of failover, the reading could be resumed from where it
+was left off. Thus we ensure there will be no duplicates or lost data. For example, if the records
+reading order is deterministic in the backend, then the split state can store the number _n_ of
+already read records to restart at _n+1_ after failover. 
+
+### SplitEnumerator and SplitEnumeratorState
+[example Cassandra SplitEnumerator](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraSplitEnumerator.java) and [SplitEnumeratorState](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorState.java)
+
+The [SplitEnumerator](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html) is responsible for creating the splits and serving them to the readers. Whenever
+possible, it is preferable to generate the splits lazily, meaning that each time a reader asks the
+enumerator for a split, the enumerator generates one on demand and assigns it to the reader. For
+that we implement [SplitEnumerator#handleSplitRequest()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#handleSplitRequest-int-java.lang.String-). Lazy splits generation is preferable to
+splits discovery, in which we pre-generate all the splits and store them waiting to assign them to
+the readers. Indeed, in some situations, the number of splits can be enormous at consume a lot a
+memory which could be problematic in case of straggling readers. The framework offers the ability to
+act upon reader registration by implementing [addReader()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addReader-int-) but, as we do lazy splits generation, we
+have nothing to do there. In some case, generating a split is too costly, so we can pre-generate a
+batch (not all) of splits to amortize this cost. the number/size of batched splits need to be taken
+into account to avoid consuming too much memory.
+
+Long story short, the tricky part of the source implementation is splitting the source data. The
+good equilibrium to find is not to have to many splits (which could lead to too much memory
+consumption) nor too few (which could lead to sub-optimal parallelism). One good way to meet this
+equilibrium is to evaluate the size of the source data upfront and allow the user to specify the
+maximum memory a split will take. That way he can configure this parameter accordingly to the memory
+available on the task managers. Of course, the size of the source data needs to be evaluated without
+reading the actual data. For the Cassandra connector it was done [like this](https://echauchot.blogspot.com/2023/03/cassandra-evaluate-table-size-without.html). The general rule of thumb
+regarding splitting is to let the user some freedom but protect him from unwanted behavior: if he
+wants to process a 1GB table in 1MB splits with 1 subtask he should be free to do so. But, as we
+allow the user to set a max split size, we should still ensure it is not too small to avoid having
+too many splits, we must also provide a default maximum. For these safety measures, rigid thresholds
+don't work well as the source my start to fail when the thresholds are suddenly exceeded.
+
+Another important topic is state. If the job manager fails, the split enumerator needs to recover.
+For that, as for the split, we need to provide a state for the enumerator (that will be part of a
+checkpoint) and return it when [SplitEnumerator#snapshotState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#snapshotState-long-) is called. Here also the
+SplitEnumerator is to be considered immutable. Any update to the state of the SplitEnumerator, must
+be done in the associated [SplitEnumeratorState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html). So, we don't create the state when snapshotState()
+is called but rather in the enumerator's constructor and return it in snapshotState(). The state
+must contain everything needed to resume where the enumerator was left off after failover . In lazy
+split generation scenario, the state will contain everything needed to generate the next split
+whenever asked to. It can be for example the start offset of next split, split size, number of
+splits still to generate etc... But the SplitEnumeratorState must also contain a list of splits, not
+the list of discovered splits, but a list of splits to reassign. Indeed, whenever a reader fails, if
+it was assigned splits after last chekpoint, then the checkpoint will not contain those splits.
+Consequently, upon restoration, the reader won't have the splits assigned anymore. There is a
+callback to deal with that case: [addSplitsBack()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addSplitsBack-java.util.List-int-). There, the splits that were assigned to the
+failing reader, can be put back into the enumerator state for later re-assignment to readers. There
+is no memory size risk here as the number of splits to reassign is pretty low.
+
+The above topics are the more important regarding splitting. There are 2 methods left to implement:
+the usual [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#start--)/[close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#close--) methods for resources creation/disposal. Regarding implementing start(),
+the Flink connector framework provides [enumeratorContext#callAsync()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumeratorContext.html#callAsync-java.util.concurrent.Callable-java.util.function.BiConsumer-long-long-) utility to run long processing
+asynchronously such as splits preparation or splits discovery (if lazy splits generation is
+impossible).
+
+### SplitReader
+[example Cassandra SplitReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSplitReader.java)
+
+This class is responsible for reading the actual splits that it receives when the framework
+calls [handleSplitsChanges()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html#handleSplitsChanges-org.apache.flink.connector.base.source.reader.splitreader.SplitsChange-)
+. The main part of the split reader is
+the [fetch()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html#fetch--)
+implementation where we read all the splits received and return the read records as
+a [RecordsBySplits](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/RecordsBySplits.html)
+object. This object contains a map of the split ids to the belonging records and also the ids of the
+finished splits. Important points need to be considered:
+
+* The fetch call must be non-blocking. If any call in its code is synchronous and potentially long, an
+escape from the fetch() must be provided. When the framework calls [wakeUp()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html#wakeUp--) we should interrupt the
+fetch for example by setting an AtomicBoolean.
+* Fetch call needs to be re-entrant: an already read split must not be re-read. We should remove it
+from the list of splits to read and add its id to the finished splits (along with empty splits) in
+the RecordsBySplits that we return.
+
+It is totally fine for the implementer to exit the fetch() method early. Also a failure could
+interrupt the fetch. In both cases the framework will call fetch() again later on. In that case, the
+fetch method must resume the reading from where it was left off using the split state already
+discussed. If resuming the read of a split is impossible because of backend constraints, then the
+only solution is to read splits atomically (either not read the split at all, or read it entirely).
+That way, in case of interrupted fetch, nothing will be output and the split could be read again
+from the beginning at next fetch call leading to no duplicates. But if the split is read entirely,
+there are points to consider:
+* We should ensure that the total split content (records from the source) fits in memory for example
+by specifying a max split size in bytes (see [SplitEnumarator](#splitenumerator-and-splitenumeratorstate))
+* The split state becomes useless, only a Split class is needed
+
+### RecordEmitter
+[example Cassandra RecordEmitter](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraRecordEmitter.java)
+
+The SplitReader reads records in the form of [an intermediary record format](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html) that the implementer
+provides for each record. It can be the raw format returned by the backend or any format allowing to
+extract the actual record afterwards. This format is not the final output format expected by the
+source. It contains anything needed to do the conversion to the record output format. We need to
+implement [RecordEmitter#emitRecord()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/RecordEmitter.html#emitRecord-E-org.apache.flink.api.connector.source.SourceOutput-SplitStateT-) to do this conversion. A good pattern here is to initialize the
+RecordEmitter with a mapping Function. The implementation must be idempotent. Indeed the method
+maybe interrupted in the middle. In that case, the same set of records will be passed to the record
+emitter again later.
+
+### Serializers
+[example Cassandra SplitSerializer](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplitSerializer.java)
+and [SplitEnumeratorStateSerializer](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorStateSerializer.java)
+
+We need to provide singleton serializers for:
+
+* Split: splits are serialized when sending them from enumerator to reader, and when checkpointing
+  the reader's current state
+* SplitEnumeratorState:  the serializer is used for the result of the
+  SplitEnumerator#snapshotState()
+
+For both, we need to implement [SimpleVersionedSerializer](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/core/io/SimpleVersionedSerializer.html)
+. Care needs to be taken at some important points:
+
+* Using Java serialization is [forbidden](https://flink.apache.org/contributing/code-style-and-quality-java.html#java-serialization)
+  in Flink mainly for migration concerns. We should rather manually write the fields of the objects
+  using ObjectOutputStream. When a class is not supported by the ObjectOutputStream (not String,
+  Integer, Long...), we should write the size of the object in bytes as an Integer and then write
+  the object converted to byte[]. Similar method is used to serialize collections. First write the
+  number of elements of the collection, then serialize all the contained objects. Of course, for
+  deserialization we do the exact same reading with the same order.
+* Flink provides a helpful utility for serde: [IOUtils](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/util/IOUtils.html).
+* There can be a lot of splits, so we should cache the OuputStream used in SplitSerializer. We can

Review Comment:
   ```suggestion
   * There can be a lot of splits, so we should cache the OutputStream used in SplitSerializer. We can
   ```



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.
+
+What we have left to do in the SourceReader class is:
+* Provide a [SplitReader](#splitreader) supplier
+* Create a [RecordEmitter](#recordemitter)
+* Create the shared resources for the SplitReaders (sessions, etc...). As the SplitReader supplier is
+created in the SourceReader constructor in a super() call, using a SourceReader factory to create
+the shared resources and pass them to the supplier seems a good idea.
+* Implement [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html#start--): here we should ask the enumerator for our first split
+* Override [close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#close--) in SourceReaderBase parent class to free up any created resources (the shared
+resources for example)
+* Implement [initializedState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#initializedState-SplitT-) to create a mutable [SplitState](#split-and-splitstate) from a Split
+* Implement [toSplitType()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#toSplitType-java.lang.String-SplitStateT-) to create a Split from the mutable SplitState
+* Implement [onSplitFinished()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#onSplitFinished-java.util.Map-): here, as it is a batch source (finite data), we should ask the
+Enumerator for next split
+
+### Split and SplitState
+[example Cassandra Split](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplit.java)
+
+The [SourceSplit](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceSplit.html) represents a partition of the source data. What defines a split depends on the
+backend we are reading from. It could be a _(partition start, partition end)_ tuple or an _(offset,
+split size)_ tuple for example.
+
+In any case, the Split object should be seen as an immutable object: any update to it should be done
+on the associated [SplitState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html). The split state is the one that will be stored inside the Flink
+[checkpoints](https://nightlies.apache.org/flink/flink-docs-master/docs/concepts/stateful-stream-processing/#checkpointing). A checkpoint may happen between 2 fetches for 1 split. So, if we're reading a split, we
+must store in the split state the current state of the reading process. This current state needs to
+be something serializable (because it will be part of a checkpoint) and something that the backend
+source can resume from. That way, in case of failover, the reading could be resumed from where it
+was left off. Thus we ensure there will be no duplicates or lost data. For example, if the records
+reading order is deterministic in the backend, then the split state can store the number _n_ of
+already read records to restart at _n+1_ after failover. 
+
+### SplitEnumerator and SplitEnumeratorState
+[example Cassandra SplitEnumerator](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraSplitEnumerator.java) and [SplitEnumeratorState](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorState.java)
+
+The [SplitEnumerator](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html) is responsible for creating the splits and serving them to the readers. Whenever
+possible, it is preferable to generate the splits lazily, meaning that each time a reader asks the
+enumerator for a split, the enumerator generates one on demand and assigns it to the reader. For
+that we implement [SplitEnumerator#handleSplitRequest()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#handleSplitRequest-int-java.lang.String-). Lazy splits generation is preferable to
+splits discovery, in which we pre-generate all the splits and store them waiting to assign them to
+the readers. Indeed, in some situations, the number of splits can be enormous at consume a lot a
+memory which could be problematic in case of straggling readers. The framework offers the ability to
+act upon reader registration by implementing [addReader()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addReader-int-) but, as we do lazy splits generation, we
+have nothing to do there. In some case, generating a split is too costly, so we can pre-generate a
+batch (not all) of splits to amortize this cost. the number/size of batched splits need to be taken
+into account to avoid consuming too much memory.
+
+Long story short, the tricky part of the source implementation is splitting the source data. The
+good equilibrium to find is not to have to many splits (which could lead to too much memory
+consumption) nor too few (which could lead to sub-optimal parallelism). One good way to meet this
+equilibrium is to evaluate the size of the source data upfront and allow the user to specify the
+maximum memory a split will take. That way he can configure this parameter accordingly to the memory
+available on the task managers. Of course, the size of the source data needs to be evaluated without
+reading the actual data. For the Cassandra connector it was done [like this](https://echauchot.blogspot.com/2023/03/cassandra-evaluate-table-size-without.html). The general rule of thumb
+regarding splitting is to let the user some freedom but protect him from unwanted behavior: if he
+wants to process a 1GB table in 1MB splits with 1 subtask he should be free to do so. But, as we
+allow the user to set a max split size, we should still ensure it is not too small to avoid having
+too many splits, we must also provide a default maximum. For these safety measures, rigid thresholds
+don't work well as the source my start to fail when the thresholds are suddenly exceeded.
+
+Another important topic is state. If the job manager fails, the split enumerator needs to recover.
+For that, as for the split, we need to provide a state for the enumerator (that will be part of a
+checkpoint) and return it when [SplitEnumerator#snapshotState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#snapshotState-long-) is called. Here also the
+SplitEnumerator is to be considered immutable. Any update to the state of the SplitEnumerator, must
+be done in the associated [SplitEnumeratorState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html). So, we don't create the state when snapshotState()
+is called but rather in the enumerator's constructor and return it in snapshotState(). The state
+must contain everything needed to resume where the enumerator was left off after failover . In lazy
+split generation scenario, the state will contain everything needed to generate the next split
+whenever asked to. It can be for example the start offset of next split, split size, number of
+splits still to generate etc... But the SplitEnumeratorState must also contain a list of splits, not
+the list of discovered splits, but a list of splits to reassign. Indeed, whenever a reader fails, if
+it was assigned splits after last chekpoint, then the checkpoint will not contain those splits.
+Consequently, upon restoration, the reader won't have the splits assigned anymore. There is a
+callback to deal with that case: [addSplitsBack()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addSplitsBack-java.util.List-int-). There, the splits that were assigned to the
+failing reader, can be put back into the enumerator state for later re-assignment to readers. There
+is no memory size risk here as the number of splits to reassign is pretty low.
+
+The above topics are the more important regarding splitting. There are 2 methods left to implement:
+the usual [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#start--)/[close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#close--) methods for resources creation/disposal. Regarding implementing start(),
+the Flink connector framework provides [enumeratorContext#callAsync()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumeratorContext.html#callAsync-java.util.concurrent.Callable-java.util.function.BiConsumer-long-long-) utility to run long processing
+asynchronously such as splits preparation or splits discovery (if lazy splits generation is
+impossible).
+
+### SplitReader
+[example Cassandra SplitReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSplitReader.java)
+
+This class is responsible for reading the actual splits that it receives when the framework
+calls [handleSplitsChanges()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html#handleSplitsChanges-org.apache.flink.connector.base.source.reader.splitreader.SplitsChange-)
+. The main part of the split reader is
+the [fetch()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html#fetch--)
+implementation where we read all the splits received and return the read records as
+a [RecordsBySplits](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/RecordsBySplits.html)
+object. This object contains a map of the split ids to the belonging records and also the ids of the
+finished splits. Important points need to be considered:
+
+* The fetch call must be non-blocking. If any call in its code is synchronous and potentially long, an
+escape from the fetch() must be provided. When the framework calls [wakeUp()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html#wakeUp--) we should interrupt the
+fetch for example by setting an AtomicBoolean.
+* Fetch call needs to be re-entrant: an already read split must not be re-read. We should remove it
+from the list of splits to read and add its id to the finished splits (along with empty splits) in
+the RecordsBySplits that we return.
+
+It is totally fine for the implementer to exit the fetch() method early. Also a failure could
+interrupt the fetch. In both cases the framework will call fetch() again later on. In that case, the
+fetch method must resume the reading from where it was left off using the split state already
+discussed. If resuming the read of a split is impossible because of backend constraints, then the
+only solution is to read splits atomically (either not read the split at all, or read it entirely).
+That way, in case of interrupted fetch, nothing will be output and the split could be read again
+from the beginning at next fetch call leading to no duplicates. But if the split is read entirely,
+there are points to consider:
+* We should ensure that the total split content (records from the source) fits in memory for example
+by specifying a max split size in bytes (see [SplitEnumarator](#splitenumerator-and-splitenumeratorstate))
+* The split state becomes useless, only a Split class is needed
+
+### RecordEmitter
+[example Cassandra RecordEmitter](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraRecordEmitter.java)
+
+The SplitReader reads records in the form of [an intermediary record format](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html) that the implementer
+provides for each record. It can be the raw format returned by the backend or any format allowing to
+extract the actual record afterwards. This format is not the final output format expected by the
+source. It contains anything needed to do the conversion to the record output format. We need to
+implement [RecordEmitter#emitRecord()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/RecordEmitter.html#emitRecord-E-org.apache.flink.api.connector.source.SourceOutput-SplitStateT-) to do this conversion. A good pattern here is to initialize the
+RecordEmitter with a mapping Function. The implementation must be idempotent. Indeed the method
+maybe interrupted in the middle. In that case, the same set of records will be passed to the record
+emitter again later.
+
+### Serializers
+[example Cassandra SplitSerializer](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplitSerializer.java)
+and [SplitEnumeratorStateSerializer](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorStateSerializer.java)
+
+We need to provide singleton serializers for:
+
+* Split: splits are serialized when sending them from enumerator to reader, and when checkpointing
+  the reader's current state
+* SplitEnumeratorState:  the serializer is used for the result of the
+  SplitEnumerator#snapshotState()
+
+For both, we need to implement [SimpleVersionedSerializer](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/core/io/SimpleVersionedSerializer.html)
+. Care needs to be taken at some important points:
+
+* Using Java serialization is [forbidden](https://flink.apache.org/contributing/code-style-and-quality-java.html#java-serialization)
+  in Flink mainly for migration concerns. We should rather manually write the fields of the objects
+  using ObjectOutputStream. When a class is not supported by the ObjectOutputStream (not String,
+  Integer, Long...), we should write the size of the object in bytes as an Integer and then write
+  the object converted to byte[]. Similar method is used to serialize collections. First write the
+  number of elements of the collection, then serialize all the contained objects. Of course, for
+  deserialization we do the exact same reading with the same order.
+* Flink provides a helpful utility for serde: [IOUtils](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/util/IOUtils.html).

Review Comment:
   It may have been a mistake to use this method in the connector because it's not part of the public API.
   
   I'll open a PR to fix that...



##########
docs/content/posts/2023-04-13-howto-create-batch-source.md:
##########
@@ -0,0 +1,221 @@
+---
+title:  "Howto create a batch source with the new Source framework"
+date: "2023-04-13T08:00:00.000Z"
+authors:
+- echauchot:
+  name: "Etienne Chauchot"
+  twitter: "echauchot"
+aliases:
+- /2023/04/13/howto-create-batch-source.html
+---
+
+## Introduction
+
+Flink community has
+designed [a new Source framework](https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/sources/)
+based
+on [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface)
+lately. Some connectors have migrated to this new framework. This article is an howto create a batch
+source using this new framework. It was built while implementing
+the [Flink batch source](https://github.com/apache/flink-connector-cassandra/commit/72e3bef1fb9ee6042955b5e9871a9f70a8837cca)
+for [Cassandra](https://cassandra.apache.org/_/index.html). I felt it could be useful to people
+interested in contributing or migrating connectors.
+
+## Implementing the source components
+
+The aim here is not to duplicate the official documentation. For details you should read the
+documentation, the javadocs or the Cassandra connector code. The links are above. The goal here is
+to give field feedback on how to implement the different components.
+
+The source architecture is depicted in the diagrams below:
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_components.svg)
+
+![](/img/blog/2023-04-13-howto-create-batch-source/source_reader.svg)
+
+### Source
+[example Cassandra Source](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/CassandraSource.java)
+
+The source interface only does the "glue" between all the other components. Its role is to
+instantiate all of them and to define the source [Boundedness](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/Boundedness.html). We also do the source configuration
+here along with user configuration validation.
+
+### SourceReader
+[example Cassandra SourceReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSourceReader.java)
+
+As shown in the graphic above, the instances of the [SourceReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html) (which we will call simply readers
+in the continuation of this article) run in parallel in task managers to read the actual data which
+is divided into [Splits](#split-and-splitstate). Readers request splits from the [SplitEnumerator](#splitenumerator-and-splitenumeratorstate) and the resulting splits are
+assigned to them in return.
+
+Luckily for us Flink provides the [SourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html) implementation that takes care of the
+synchronization between the readers and the main thread. Flink also provides a useful extension to
+this class for most cases: [SingleThreadMultiplexSourceReaderBase](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SingleThreadMultiplexSourceReaderBase.html). This class avoids having to
+specify the threading model as it is already configured to read splits with one thread using one
+[SplitReader](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html). This is not harmful to the performance of the source as the SourceReaders run in
+parallel among the task managers.
+
+What we have left to do in the SourceReader class is:
+* Provide a [SplitReader](#splitreader) supplier
+* Create a [RecordEmitter](#recordemitter)
+* Create the shared resources for the SplitReaders (sessions, etc...). As the SplitReader supplier is
+created in the SourceReader constructor in a super() call, using a SourceReader factory to create
+the shared resources and pass them to the supplier seems a good idea.
+* Implement [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceReader.html#start--): here we should ask the enumerator for our first split
+* Override [close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#close--) in SourceReaderBase parent class to free up any created resources (the shared
+resources for example)
+* Implement [initializedState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#initializedState-SplitT-) to create a mutable [SplitState](#split-and-splitstate) from a Split
+* Implement [toSplitType()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#toSplitType-java.lang.String-SplitStateT-) to create a Split from the mutable SplitState
+* Implement [onSplitFinished()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html#onSplitFinished-java.util.Map-): here, as it is a batch source (finite data), we should ask the
+Enumerator for next split
+
+### Split and SplitState
+[example Cassandra Split](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplit.java)
+
+The [SourceSplit](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SourceSplit.html) represents a partition of the source data. What defines a split depends on the
+backend we are reading from. It could be a _(partition start, partition end)_ tuple or an _(offset,
+split size)_ tuple for example.
+
+In any case, the Split object should be seen as an immutable object: any update to it should be done
+on the associated [SplitState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/SourceReaderBase.html). The split state is the one that will be stored inside the Flink
+[checkpoints](https://nightlies.apache.org/flink/flink-docs-master/docs/concepts/stateful-stream-processing/#checkpointing). A checkpoint may happen between 2 fetches for 1 split. So, if we're reading a split, we
+must store in the split state the current state of the reading process. This current state needs to
+be something serializable (because it will be part of a checkpoint) and something that the backend
+source can resume from. That way, in case of failover, the reading could be resumed from where it
+was left off. Thus we ensure there will be no duplicates or lost data. For example, if the records
+reading order is deterministic in the backend, then the split state can store the number _n_ of
+already read records to restart at _n+1_ after failover. 
+
+### SplitEnumerator and SplitEnumeratorState
+[example Cassandra SplitEnumerator](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraSplitEnumerator.java) and [SplitEnumeratorState](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorState.java)
+
+The [SplitEnumerator](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html) is responsible for creating the splits and serving them to the readers. Whenever
+possible, it is preferable to generate the splits lazily, meaning that each time a reader asks the
+enumerator for a split, the enumerator generates one on demand and assigns it to the reader. For
+that we implement [SplitEnumerator#handleSplitRequest()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#handleSplitRequest-int-java.lang.String-). Lazy splits generation is preferable to
+splits discovery, in which we pre-generate all the splits and store them waiting to assign them to
+the readers. Indeed, in some situations, the number of splits can be enormous at consume a lot a
+memory which could be problematic in case of straggling readers. The framework offers the ability to
+act upon reader registration by implementing [addReader()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addReader-int-) but, as we do lazy splits generation, we
+have nothing to do there. In some case, generating a split is too costly, so we can pre-generate a
+batch (not all) of splits to amortize this cost. the number/size of batched splits need to be taken
+into account to avoid consuming too much memory.
+
+Long story short, the tricky part of the source implementation is splitting the source data. The
+good equilibrium to find is not to have to many splits (which could lead to too much memory
+consumption) nor too few (which could lead to sub-optimal parallelism). One good way to meet this
+equilibrium is to evaluate the size of the source data upfront and allow the user to specify the
+maximum memory a split will take. That way he can configure this parameter accordingly to the memory
+available on the task managers. Of course, the size of the source data needs to be evaluated without
+reading the actual data. For the Cassandra connector it was done [like this](https://echauchot.blogspot.com/2023/03/cassandra-evaluate-table-size-without.html). The general rule of thumb
+regarding splitting is to let the user some freedom but protect him from unwanted behavior: if he
+wants to process a 1GB table in 1MB splits with 1 subtask he should be free to do so. But, as we
+allow the user to set a max split size, we should still ensure it is not too small to avoid having
+too many splits, we must also provide a default maximum. For these safety measures, rigid thresholds
+don't work well as the source my start to fail when the thresholds are suddenly exceeded.
+
+Another important topic is state. If the job manager fails, the split enumerator needs to recover.
+For that, as for the split, we need to provide a state for the enumerator (that will be part of a
+checkpoint) and return it when [SplitEnumerator#snapshotState()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#snapshotState-long-) is called. Here also the
+SplitEnumerator is to be considered immutable. Any update to the state of the SplitEnumerator, must
+be done in the associated [SplitEnumeratorState](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html). So, we don't create the state when snapshotState()
+is called but rather in the enumerator's constructor and return it in snapshotState(). The state
+must contain everything needed to resume where the enumerator was left off after failover . In lazy
+split generation scenario, the state will contain everything needed to generate the next split
+whenever asked to. It can be for example the start offset of next split, split size, number of
+splits still to generate etc... But the SplitEnumeratorState must also contain a list of splits, not
+the list of discovered splits, but a list of splits to reassign. Indeed, whenever a reader fails, if
+it was assigned splits after last chekpoint, then the checkpoint will not contain those splits.
+Consequently, upon restoration, the reader won't have the splits assigned anymore. There is a
+callback to deal with that case: [addSplitsBack()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#addSplitsBack-java.util.List-int-). There, the splits that were assigned to the
+failing reader, can be put back into the enumerator state for later re-assignment to readers. There
+is no memory size risk here as the number of splits to reassign is pretty low.
+
+The above topics are the more important regarding splitting. There are 2 methods left to implement:
+the usual [start()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#start--)/[close()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumerator.html#close--) methods for resources creation/disposal. Regarding implementing start(),
+the Flink connector framework provides [enumeratorContext#callAsync()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/api/connector/source/SplitEnumeratorContext.html#callAsync-java.util.concurrent.Callable-java.util.function.BiConsumer-long-long-) utility to run long processing
+asynchronously such as splits preparation or splits discovery (if lazy splits generation is
+impossible).
+
+### SplitReader
+[example Cassandra SplitReader](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraSplitReader.java)
+
+This class is responsible for reading the actual splits that it receives when the framework
+calls [handleSplitsChanges()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html#handleSplitsChanges-org.apache.flink.connector.base.source.reader.splitreader.SplitsChange-)
+. The main part of the split reader is
+the [fetch()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html#fetch--)
+implementation where we read all the splits received and return the read records as
+a [RecordsBySplits](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/RecordsBySplits.html)
+object. This object contains a map of the split ids to the belonging records and also the ids of the
+finished splits. Important points need to be considered:
+
+* The fetch call must be non-blocking. If any call in its code is synchronous and potentially long, an
+escape from the fetch() must be provided. When the framework calls [wakeUp()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html#wakeUp--) we should interrupt the
+fetch for example by setting an AtomicBoolean.
+* Fetch call needs to be re-entrant: an already read split must not be re-read. We should remove it
+from the list of splits to read and add its id to the finished splits (along with empty splits) in
+the RecordsBySplits that we return.
+
+It is totally fine for the implementer to exit the fetch() method early. Also a failure could
+interrupt the fetch. In both cases the framework will call fetch() again later on. In that case, the
+fetch method must resume the reading from where it was left off using the split state already
+discussed. If resuming the read of a split is impossible because of backend constraints, then the
+only solution is to read splits atomically (either not read the split at all, or read it entirely).
+That way, in case of interrupted fetch, nothing will be output and the split could be read again
+from the beginning at next fetch call leading to no duplicates. But if the split is read entirely,
+there are points to consider:
+* We should ensure that the total split content (records from the source) fits in memory for example
+by specifying a max split size in bytes (see [SplitEnumarator](#splitenumerator-and-splitenumeratorstate))
+* The split state becomes useless, only a Split class is needed
+
+### RecordEmitter
+[example Cassandra RecordEmitter](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/reader/CassandraRecordEmitter.java)
+
+The SplitReader reads records in the form of [an intermediary record format](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/splitreader/SplitReader.html) that the implementer
+provides for each record. It can be the raw format returned by the backend or any format allowing to
+extract the actual record afterwards. This format is not the final output format expected by the
+source. It contains anything needed to do the conversion to the record output format. We need to
+implement [RecordEmitter#emitRecord()](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/connector/base/source/reader/RecordEmitter.html#emitRecord-E-org.apache.flink.api.connector.source.SourceOutput-SplitStateT-) to do this conversion. A good pattern here is to initialize the
+RecordEmitter with a mapping Function. The implementation must be idempotent. Indeed the method
+maybe interrupted in the middle. In that case, the same set of records will be passed to the record
+emitter again later.
+
+### Serializers
+[example Cassandra SplitSerializer](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/split/CassandraSplitSerializer.java)
+and [SplitEnumeratorStateSerializer](https://github.com/apache/flink-connector-cassandra/blob/d92dc8d891098a9ca6a7de6062b4630079beaaef/flink-connector-cassandra/src/main/java/org/apache/flink/connector/cassandra/source/enumerator/CassandraEnumeratorStateSerializer.java)
+
+We need to provide singleton serializers for:
+
+* Split: splits are serialized when sending them from enumerator to reader, and when checkpointing
+  the reader's current state
+* SplitEnumeratorState:  the serializer is used for the result of the
+  SplitEnumerator#snapshotState()
+
+For both, we need to implement [SimpleVersionedSerializer](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/core/io/SimpleVersionedSerializer.html)
+. Care needs to be taken at some important points:
+
+* Using Java serialization is [forbidden](https://flink.apache.org/contributing/code-style-and-quality-java.html#java-serialization)
+  in Flink mainly for migration concerns. We should rather manually write the fields of the objects
+  using ObjectOutputStream. When a class is not supported by the ObjectOutputStream (not String,
+  Integer, Long...), we should write the size of the object in bytes as an Integer and then write
+  the object converted to byte[]. Similar method is used to serialize collections. First write the
+  number of elements of the collection, then serialize all the contained objects. Of course, for
+  deserialization we do the exact same reading with the same order.
+* Flink provides a helpful utility for serde: [IOUtils](https://nightlies.apache.org/flink/flink-docs-master/api/java/org/apache/flink/util/IOUtils.html).
+* There can be a lot of splits, so we should cache the OuputStream used in SplitSerializer. We can
+  do so by using.
+
+`  ThreadLocal<DataOutputSerializer> SERIALIZER_CACHE =
+  ThreadLocal.withInitial(() -> new DataOutputSerializer(64));`
+
+The initial stream size depends on the size of a split. 
+
+## Testing the source
+
+For the sake of concision of this article, testing the source will be the object of the next article. Stay tuned !
+
+## Conclusion
+
+This article gathering the implementation field feedback was needed as the javadocs cannot cover all
+the implementation details for high-performance and maintainable sources. I hope you enjoyed reading
+and that it gave you the envy to contribute a new connector to the Flink project !

Review Comment:
   ```suggestion
   and that it gave you the desire to contribute a new connector to the Flink project !
   ```



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